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Record W1879560388

Design and characterization of a 6 × 6 planar reconfigurable transmitarray

2010· article· en· W1879560388 on OpenAlexaff
Jonathan Y. Lau, Sean V. Hum

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsVaricapReconfigurabilityPlanarBeamformingFabricationMaterials scienceWaveguideOpticsAperture (computer memory)Characterization (materials science)OptoelectronicsElectronic engineeringComputer scienceEngineeringAcousticsCapacitancePhysicsTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

This paper presents the design and experimental characterization of a planar 6×6 fully reconfigurable transmitarray at 5.7 GHz. First, the design of the array element, which consists of two varactor diode-loaded patches coupled by a varactor diode-loaded slot, is presented. The design is optimized by full-wave simulation, followed by experimental characterization in waveguide. The element exhibits the behavior of a third-order tunable filter and achieves 245 degrees of phase agility with less than 3 dB of variation in transmission magnitude in the tuning range. Next, the design and fabrication of a planar array is described, and the varactor biasing scheme is discussed in detail. Finally, two-dimensional beamforming results are presented. Not only is this transmitarray able to demonstrate full two-dimensional reconfigurability and beamforming as an array lens, it is also low-profile, low-cost, and easy to fabricate, making it very attractive for applications where high-gain beam-scanning is needed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.345
Threshold uncertainty score0.156

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.195
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2010
Admission routes1
Has abstractyes

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